Relative Forage Quality
This article reviews the benefits and challenges inherent with a new forage lab technique proposed for quality analysis.At first past, I see several weaknesses in using the new system. First, it will require greater expense and time in conducting analyses. Second, the small gains in analytical accuracy will likely be overshadowed by unavoidable sampling variability.
The in vitro digestibility assays have been used for decades (since
1964) and they too were subject to errors. These errors are unavoidable and
will be retained in the analysis system even if NIR is used to conduct the analyses.
Finally, where is the evidence that we need a new system? I assume that cows
are producing at all-time high levels, and we are likely getting all we can
out of alfalfa, given the fact that our major problem with analysis is accounting
for variability in the final product.
You can see my biases here. Even so, the new procedures will likely become the
standard if the dairy industry decides it provides better data for ration balancing
purposes, even if it really doesn't. The following article gives a brief explanation
of the procedures and some general background. If you hear of labs that are
going to offer the test, let me know.
Relative Forage Quality
Indexing Legumes and Grasses for Forage Quality
The Relative Forage Quality lab analysis and calculation procedure is presented in this article
Relative Feed Value (RFV) has been of great value in ranking forages for sale or inventorying and assigning forage to animal groups according to their quality needs. With the introduction of the new approaches to determining animal requirements in National Research Council Nutrient Requirements for Dairy Cattle (2001), there is an opportunity to improve upon this quality index through use of newer analyses and equations.
Relative Feed Value was based on the concept of digestible dry matter intake relative to a standard forage according to the following:
RFV = (DMI, % of BW) * (DDM, % of DM) / 1.29Where:
DMI = dry matter intake
DDM = digestible dry matter
BW = body weight
Dry matter intake was estimated from NDF and DDM from acid detergent
fiber. The constant, 1.29, was chosen so that RFV = 100 for full bloom alfalfa.
The constant was the expected DDM intake, as % of BW, for full-bloom alfalfa
based on animal data.
We propose to keep the same concept and format for Relative Forage Quality (RFQ)
except that Total Digestable Nutrients (TDN) will be used rather than DDM. Thus
RFQ will be as follow:
RFQ = (DMI, % of BW) * (TDN, % of DM) / 1.23
Where the divisor, 1.23, is used to adjust the equation to have
a mean and range similar to RFV (Moore and Undersander, 2002).
Total digestible nutrients are calculated from the new NRC recommendations using
in vitro estimates of digestible NDF as follows:
TDN= [(NFC*.98) + (CP*.93) + (FA*.97*2.25) +(NDF * (NDFD*.75/100)] – 7 (NRC, 2001)
Where:
CP = crude protein (% of DM)
EE = ether extract (% of DM)
FA = fatty acids (% of DM) = ether extract - 1
NDF = Neutral detergent fiber (% of DM)
NDFD = 48-hour in vitro NDF digestibility (% of NDF)
NFC = non fibrous carbohydrate
(% of DM) = 100 – (NDF+CP+EE+ash)
Dry matter intake calculations will vary for different forage types. Currently, two forage types are recognized:
1) Alfalfa, clovers, and legume/grass mixtures where dry matter intake is estimated as:
DMI = ((.0120 *1350 / (NDF/100)) + (NDFD – 45) * .374) / 1350 * 100 (Mertens, 1987 with NDFD adjustment proposed by Oba and Allen (1999). 45 is an average value for fiber digestibility of alfalfa and alfalfa/grass mixtures.
Where DMI is expressed as % of body weight (BW), NDF as % of DM and NDFD as % of NDF.
2) Warm and cool season grasses where dry matter intake is estimated as:
DMI = -2.318 + 0.442*CP -0.0100*CP2 - 0.0638*TDN + 0.000922*TDN2 + 0.180*ADF - 0.00196*ADF2 - 0.00529*CP*ADF
Where DMI is expressed as % of BW, and CP, ADF, and TDN are expressed as % of DM (Moore and Kunkle, 1999).
|
References
Mertens, D. R. 1987. Predicting intake and digestibility using mathematical models of ruminal function. J. Anim. Sci. 64:1548-1558.
Moore, J.E., and W.E. Kunkle. 1999. Evaluation of equations
for estimating voluntary intake of forages and forage-based diets. J. Animal
Sci. (Suppl. 1):204.
Moore, J. E. and D. J. Undersander, 2002. Relative Forage Quality: An alternative
to relative feed value and quality index. p. 16-31 In: Proc. Florida Ruminant
Nutrition Symposium, January 10-11, University of Florida, Gainesville.
National Research Council. 2001. Nutrient requirements of dairy cattle. 7th rev. ed. Natl. Acad. Sci., Washington D.C.
Oba, M. and M. S. Allen. 1999. Evaluation of the importance of the digestibility of neutral detergent fiber from forage: effects on dry matter intake and milk yield of dairy cows. J. Dairy Sci. 82:589-596.
